Songtao Wu
ABSTRACT
Steganography is the art of hiding information in ways that prevents the detection of hidden messages. Image steganography, which hides messages into a cover image for secret transmission, attracts increasing attention in social media era. Currently, most works focus on designing message embedding algorithms to avoid the stego images being distinguished from normal ones via visual observation or statistical analysis. This paper aims to make the detection of the stego images more difficult by selecting the suitable cover images. We propose a new measure to evaluate the hiding ability of the cover image based on Fisher Information Matrix and Gaussian Mixture Model. Experiments on standard dataset validate that the cover image with good hiding ability can improve the performance of various steganography algorithms obviously. Moreover, the proposed measure provides a statistical explanation of the existing cover image selection techniques and shows better performance against steganalysis.
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Index Terms
- What makes the stego image undetectable?
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